Cross-omics data analyses and integration in precision health. (R-11733)

This project proposes to deal with the differentiation between health and disease in a more sustainable way through the early detection of signals, markers, or patterns that indicate harmful events, before the disease can develop. Recent progress in life sciences and technology allows us to map the genetic, proteomic and metabolic profile of individuals, revealing millions of molecular underpinnings of a sample and the individual it originates from. The proposed approach of this project is to use computational methods, to integrate and visualize various levels of personal biomedical data at different scales and over time to describe individual health at the molecular level. A visual analytics approach to represent multi-omics data as a molecular & phenotypical network evolving from one state to another will be used in this explorative project. The ambition is to report the dynamics of various (levels of) biomarkers and describe their longitudinal interactions. We believe this will allow us to map dynamical molecular systems, leading to new insights in the molecular dynamics between health and (chronic) disease. For this project cross-omics data that is collected for a longitudinal cohort study called the I-AM frontier (IAF) study will be the main data source. In order to identify robust disease profiles UK biobank will be an additional cross sectional data resource containing the same data types as the IAF.

Keywords:Multi-omics, Network biology, NETWORKS

Disciplines:Interactomics, Bioinformatics data integration and network biology, Bioinformatics of disease, Data visualisation and high-throughput image analysis, Preventive medicine